Radio resources are scarce and their utilization is typically controlled at multiple levels of different radio network phases, such as network dimensioning (i.e., where a rough estimation of radio resource utilization is performed), detailed static network planning, network self optimization, and dynamic radio resource control functions (e.g., admission and congestion control, scheduling, and load balancing).
Balancing radio resource utilization and ensuring that a required service quality is met have always been an important consideration for wireless networks. This consideration is becoming even more crucial as traffic demand grows and various types of radio technologies must co-exist. Existing radio resources (e.g. frequency spectrum) are limited and expensive and so efficient utilization of such resources is crucial. Furthermore, increasing diversity in radio devices and radio nodes of various capabilities may require more sophisticated algorithms for evaluating resource consumption and controlling the resources utilization.
Efficient radio resource control becomes particularly challenging in heterogeneous networks where the neighbor cell sizes and capacity as well as the traffic demand may vary significantly.
Planning and optimization of wireless networks (e.g., an LTE deployment), may include managing base station location and antenna parameter configuration and algorithmic approaches for network-level performance evaluation. Finding the optimal network design and configuration requires solving a combinatorial optimization problem. To select among candidate configuration solutions, it is essential to develop system modeling techniques that enable rapid performance assessment of different configurations.
In Universal Mobile Telecommunications System (UMTS), the system modeling has been primarily based on power control, where the transmit power of each link is adjusted to meet a given signal-to-interference-and-noise ratio (SINR) threshold. By the SINR requirement, the power expenditure of one cell is a linear function in those of the other cells. As a result, the power control mechanism is represented by a system of linear equations, which is sometimes referred to as UMTS interference coupling.
An alternative approach to the power-control model is the rate-control scheme, which takes into account the traffic demand which exhibits a nonlinear relation and is thus more complex. In this scheme, the performance target is not SINR, but the amount of data to be served over a given time period. Among other advantages, this approach makes it possible to capture the effect of scheduling without the need of explicitly modeling full details of scheduling algorithms. The rate-control-based approach also allows for modeling the system behavior of non-power-controlled systems (e.g., LTE downlink). A general formulation of such a system model has been originally provided in I. Siomina, A. Furuskär and G. Fodor, “A mathematical framework for statistical QoS and capacity studies in OFDM networks,” Proceedings of IEEE PIMRC '09, September 2009, pp. 2772-2776, which is incorporated by reference herein in its entirety.
Radio network planning and optimization may be performed by specialized programs that may use radio characteristics of the target radio environment as input. Such characteristics may be collected by means of drive tests or simulated propagation modeling. Radio network planning and optimization may also be automated and implemented in the network itself (e.g., as a part of operations and maintenance (O&M) and/or self-organizing network (SON)).
Radio resource management (RRM) is a set of functionalities that allow for automatically controlling and balancing radio resource utilization among different cells of a network during the network operation. The goal of RRM algorithms is to maximize radio resource utilization efficiency and ensure the requested service quality. Specialized programs may be configured to perform automated RRM algorithms using radio characteristics of the target radio environment as input (e.g., collected via drive tests or simulated propagation modeling). RRM may be intra-frequency, inter-frequency or inter-RAT.
Some examples of RRM functions include radio bearer control (RBC), radio admission/congestion control, connection mobility control, dynamic resource allocation and packet scheduling, inter-cell interference coordination, load balancing, and others.
RBC:
The establishment, maintenance, and release of Radio Bearers involve the configuration of radio resources associated with them. When setting up a radio bearer for a service, RBC may take into account the overall resource situation in E-UTRAN, the QoS requirements of in-progress sessions, and the QoS requirement for the new service. RBC is also concerned with the maintenance of radio bearers of in-progress sessions at the change of the radio resource situation due to mobility or other reasons. RBC is involved in the release of radio resources associated with radio bearers at session termination, handover or at other occasions.
Radio Admission Control/Congestion Control:
The purpose of admission control is to determine if the requested resources are available and to reserve those resources (e.g., admit or reject the establishment requests for new radio bearers). To do this, radio admission control may consider the overall resource situation in E-UTRAN, the QoS requirements, the priority levels and the provided QoS of in-progress sessions, and the QoS requirement of the new radio bearer request. The goal of radio admission control is to ensure high radio resource utilization (by accepting radio bearer requests as long as radio resources are available) and at the same time to ensure proper QoS for in-progress sessions (by rejecting radio bearer requests when they cannot be accommodated). Admission control thus addresses the trade-off between blocking newly arriving service requests and dropping on-going services for which either the requested QoS cannot be ensured or which consume a lot of radio resources and/or have a lower priority.
Connection Mobility Control:
Connection mobility control is concerned with the management of radio resources in connection with idle or connected mode mobility. In idle mode, the cell reselection algorithms are controlled by setting parameters (e.g., thresholds and hysteresis values) that define the best cell and/or determine when the UE should select a new cell. Also, E-UTRAN broadcasts parameters that configure the UE measurement and reporting procedures. In connected mode, the mobility of radio connections has to be supported. Handover decisions may be based on UE and eNodeB measurements. In addition, handover decisions may take other inputs, such as neighbor cell load, traffic distribution, transport and hardware resources, and Operator defined policies into account.
Dynamic Resource Allocation and Packet Scheduling:
The goal of dynamic resource allocation or packet scheduling is to allocate and de-allocate resources (including buffer and processing resources and resource blocks) to user and control plane packets. Dynamic resource allocation may involve several sub-tasks, such as selecting radio bearers whose packets are to be scheduled and managing the necessary resources (e.g. the power levels or the specific resource blocks used). Packet scheduling typically takes into account the QoS requirements associated with the radio bearers, the channel quality information for UEs, buffer status, interference situation, etc. Dynamic resource allocation may also take into account restrictions or preferences on some of the available resource blocks or resource block sets due to inter-cell interference coordination considerations.
Inter-Cell Interference Coordination:
Inter-cell interference coordination (ICIC) is aimed at managing radio resources such that inter-cell interference is kept under control. The ICIC mechanism includes a frequency domain component and a time domain component. ICIC is inherently a multi-cell RRM function that needs to take into account information (e.g. the resource usage status and traffic load situation) from multiple cells. The preferred ICIC method may be different in the uplink and downlink. The frequency domain ICIC manages radio resource, notably the radio resource blocks, such that multiple cells coordinate the use of frequency domain resources. For the time domain ICIC, subframe utilization across different cells are coordinated in time through backhaul signaling or O&M configuration of so called Almost Blank Subframe patterns. Enhanced ICIC techniques are particularly crucial for heterogeneous networks where the cell assignment rule may diverge from the RSRP-based approach. For example, the divergence may be towards a pathloss- or pathgain-based approach (e.g., by means of cell range expansion when e.g. a cell may still be selected as a serving cell when its RSRP is up to ΔdB lower than the RSRP of the current serving cell). Cell range expansion is a concept that may be exercised for cells with a transmit power lower than neighbor cells, to make it possible increasing the cell coverage of low-power nodes.
Load Balancing:
Load balancing is aimed at handling uneven distribution of the traffic load over multiple cells. The purpose of load balancing is therefore to influence the load distribution in such a manner that radio resources remain highly utilized, the QoS of in-progress sessions are maintained to the extent possible, and call dropping probabilities are kept sufficiently small. Load balancing algorithms may result in handover (e.g., intra-frequency, inter-frequency, inter-RAT) or cell reselection decisions (e.g., related to frequency or carrier, RAT, reselection threshold or other reselection parameters configured by the network) aimed at redistributing traffic from highly loaded cells to underutilized cells.
In LTE, RRM functions such as those discussed above, are typically performed by an eNodeB. However, the decisions may be made via a centralized architecture (e.g., via O&M) or decentralized architecture (e.g., involving X2 interface in LTE and UE history information). There may also be semi-centralized architecture, where some of the RRM-related decisions, at least in part, are centralized and some are distributed among the radio nodes.
In performing various RRM functions, such as those described above, the system may need to perform various network management actions, such as bearer establishing/configuration/re-configuration/rejecting/dropping, handover (e.g., intra-frequency, inter-frequency, inter-RAT), parameter optimization (e.g., modify parameters related to scheduling bandwidth, transmit power level, cell selection/reselection received signal strength or quality thresholds, cell range offsets for evaluating candidates for cell reselection, other parameters used by different triggers, etc.). Such actions may be based on different parameters, such as requested and/or estimated current QoS, predicted QoS for a requested service and/or for in-service bearers, estimated current or predicted radio resource utilization (e.g., bandwidth utilization or RB utilization, average transmit power, cell load), with single or multi-RAT, estimated or configured capacity (or capacity region) or the maximum acceptable radio resource utilization, with single- or multi-RAT, and/or on other parameters.
Cell load is one of the classic measures of resource utilization in a cell and, in practice, it depends on traffic intensity and interference in the entire network. Estimating the cell load and optimizing load sharing among neighbor cells is therefore an important but challenging element of RRM algorithms. In LTE, cell load is typically associated with RB utilization, while in UMTS, cell load is typically associated with the total transmit power in a cell (Downlink DL) or the noise rise ratio (uplink UL). The estimation is typically based on network measurements and/or UE measurements. While RB utilization in LTE may be estimated over a past time period (i.e., based on averaging of the amount of utilized radio resources over the time), it may be desirable to predict and evaluate the serving or neighbor cell load for a given change (e.g., an admitted UE or expanded cell range). This and related problems are addressed by the solutions described in this disclosure.